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Disparities in medical recommendations from AI-based chatbots across different countries/regions.
Sci Rep
July 2024
Graduate Institute of Biomedical Science, China Medical University, Taichung, Taiwan.
Article Synopsis
- - This study examines the differences and advantages in healthcare information provided by AI chatbots regarding adjuvant therapy for endometrial cancer across four regions: Indonesia, Nigeria, Taiwan, and the USA, and through three platforms: Bard, Bing, and ChatGPT-3.5.
- - An analysis of chatbot responses revealed significant regional variations in quality, with Bing performing the best in Nigeria and Bard showing superior results compared to ChatGPT-3.5 across all areas assessed.
- - The findings underscore the need for further research and development to ensure equitable access to reliable AI-generated medical information, as the quality of information varies widely depending on location and the platform used.
Large language models as assistance for glaucoma surgical cases: a ChatGPT vs. Google Gemini comparison.
Graefes Arch Clin Exp Ophthalmol
September 2024
Ophthalmology Department, Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168, Rome, Italy.
Article Synopsis
- The study assessed how well ChatGPT-4 and Google Gemini could analyze detailed glaucoma cases and suggest surgical plans, utilizing 60 medical records to evaluate their performance.
- ChatGPT-4 agreed with expert glaucoma surgeons in 58% of cases, significantly outperforming Google Gemini, which only matched in 32% of cases and failed to complete tasks in 27% of scenarios.
- Overall, ChatGPT-4 demonstrated superior quality and consistency in surgical recommendations, especially in challenging cases, highlighting significant limitations with Google Gemini.
Evaluating the Accuracy of ChatGPT and Google BARD in Fielding Oculoplastic Patient Queries: A Comparative Study on Artificial versus Human Intelligence.
Ophthalmic Plast Reconstr Surg
May 2024
Division of Oculofacial Plastic and Reconstructive Surgery, Viterbi Family Department of Ophthalmology, UC San Diego Shiley Eye Institute, La Jolla, California, U.S.A.
Purpose: This study evaluates and compares the accuracy of responses from 2 artificial intelligence platforms to patients' oculoplastics-related questions.
Methods: Questions directed toward oculoplastic surgeons were collected, rephrased, and input independently into ChatGPT-3.5 and BARD chatbots, using the prompt: "As an oculoplastic surgeon, how can I respond to my patient's question?.
Large Language Models in Hematology Case Solving: A Comparative Study of ChatGPT-3.5, Google Bard, and Microsoft Bing.
Cureus
August 2023
Physiology, All India Institute of Medical Sciences, Deoghar, Deoghar, IND.
Background Large language models (LLMs), such as ChatGPT-3.5, Google Bard, and Microsoft Bing, have shown promising capabilities in various natural language processing (NLP) tasks. However, their performance and accuracy in solving domain-specific questions, particularly in the field of hematology, have not been extensively investigated.
View Article and Find Full Text PDFBARD: A Structured Technique for Group Elicitation of Bayesian Networks to Support Analytic Reasoning.
Risk Anal
June 2022
Department of Psychological Sciences, Birkbeck, University of London, London, UK.
In many complex, real-world situations, problem solving and decision making require effective reasoning about causation and uncertainty. However, human reasoning in these cases is prone to confusion and error. Bayesian networks (BNs) are an artificial intelligence technology that models uncertain situations, supporting better probabilistic and causal reasoning and decision making.
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